基于大数据分析技术的高校毕业就业预测模型

Employment Prediction Model for College Graduates Based on Big Data Analysis Technology

为了获得更优的高校毕业生就业预测结果,设计了基于大数据分析技术的高校毕业生就业预测模型。首先收集高校毕业生就业相关样本数据,将其输入到最小二乘支持向量机进行训练,拟合高校毕业生就业变化态势;然后采用蚁群算法根据高校毕业生就业变化态势对预测模型参数进行优化,构建最优的高校毕业生就业预测模型;最后与其它高校毕业生就业预测模型进行了对比测试。测试结果表明,大数据分析技术可以更好的描述高校毕业生就业变化态势,提升高校毕业生预测效果,高校毕业生就业预测速度加快,具有更高的实际应用价值。

The employment of college graduates is a complex problem.There are many related factors and the factors interact each other.The current prediction model is difficult to track the change trend of college graduates employment scientifically and objectively,it results in poor employment prediction effect of college graduates and is unable to meet the requirements of practical application.In order to obtain better employment prediction results of college graduates,this paper designs an employment prediction model for college graduates based on big data analysis technology.Firstly,we collect the sample data related to the employment of college graduates,input it into least square support vector machine for training,fit the employment change trend of college graduates.Then we use ant colony algorithm to optimize the parameters of the prediction model according to the employment change trend of college graduates,so as to build the optimal employment prediction model of college graduates.Finally,we compare with other college graduates’employment prediction models.The results show that big data analysis technology can better describe the employment change trend of college graduates,improve the prediction effect of college graduates,accelerate the employment prediction speed of college graduates,and have higher practical application value.